97 results about "Elementary particle" patented technology

A mesostructured aluminosilicate material is described, constituted by at least two spherical elementary particles, each of said spherical particles being constituted by a matrix based on silicon oxide and aluminium oxide, having a pore size in the range 1.5 to 30 nm, a Si / Al molar ratio of at least 1, having amorphous walls with a thickness in the range 1 to 20 nm, said spherical elementary particles having a maximum diameter of 10 μm. A process for preparing said material and its application in the fields of refining and petrochemistry are also described.

Aiming at the disadvantages of a basic particle swarm algorithm on the solving of the coverage optimization problem of a wireless sensor network, in combination with a maximum coverage algorithm, the invention provides a particle swarm-based coverage optimization method of a wireless sensor network mobile node. The algorithm takes a mobile node position vector quantity as an input parameter, and a network coverage rate as a target function, and the positions among nodes can be adjusted by a far module and a near module mentioned in the maximum coverage algorithm, the nodes are enabled to be far away if being distributed densely; and the nodes are enabled to be near if being distributed loosely. In combination with the position adjustment and the particle swarm algorithm, the positions of the nodes and the nearest node can be adjusted in a particle swarm algorithm speed updating formula, and the particle can be guided to be evolved, so that the coverage range of the nodes can be preferably expanded, and the capability of the particle swarm algorithm for searching the globally optimal solution can be enhanced, i.e. the network coverage rate can be improved. Finally, the wireless sensor network coverage optimization problem can be solved by the position adjustment-based particle swarm algorithm.

The invention designs a blind channel balancing method based on an improved PSO (Particle Swarm Optimization) BP (Back Propagation) neural network. In the process of solving the blind balancing problem on the basis of a BP neural network, determination of an initial weight and a threshold of the BP neural network is lack of the theoretical basis and has the defects of low convergence speed, easiness for falling into a local minimal value and the like so as to cause a poor channel blind balancing effect. In order to overcome the defects of the BP neural network and improving the channel blind balancing effect, the invention discloses a blink balancing method based on the improved PSO-BP neural network. According to the method, firstly, defects of a basic particle swarm algorithm are overcome, parameters of the basic particle swarm are improved, and an inertia weight and a learning factor are adaptively regulated; secondly, the initial weight and the threshold of the neural network are optimized by utilizing the advantage of high global searching capacity of the improved particle swarm, and then more accurate searching is carried out in such local space by utilizing a BP algorithm soas to obtain an optimal connection weight and threshold of the neural network; and finally, blind balancing based on the the improved PSO-BP neural network is implemented.

The present invention relates to a kind of pre-alloyed powder and its application in making diamond tool. The pre-alloyed powder consists of at least two selected from Fe, Co, Cu and Ni as basic components, one or several of Mn, Ti, Sn, Mo, W and WC, and one or two of RE, such as La and Ce. It contains at most 80 % of Fe, at most 40 % of Co, at most 80 % of Cu, at most 40 % of Ni, at most 8 % of M and 0-5 % of RE, where, M is one or several of Mn, Ti, Sn, Mo, W and WC and RE is La and / or Ce. The pre-alloyed powder has also inevitable impurity. Scanning electronic microscope measurement shows that the pre-alloyed powder has basic particle size smaller than 15 micron and oxygen content not more than 2 %. The pre-alloyed powder is used as adhesive in making diamond tool.

The invention relates to the technical field of reactive powder optimization of a power distribution network of a power system, and particularly relates to a tabu particle swarm algorithm based reactive power optimization method of a power distribution network. According to the situation that a basic particle swarm algorithm in the optimization process can be easily trapped in local optimization, the invention discloses the improved method by the combination of a tabu search algorithm, and the defect that the particle swarm algorithm can be easily trapped in local optimum is overcome by utilizing the memory function and the characteristic of high climbing ability of the search algorithm; meanwhile, learning factors c1 and c2 which change as the increase of iterations and an inertia weight coefficient Omega are introduced in a particle position and a speed upgrading equation of the particle swarm algorithm, and the problem that the particle swarm algorithm can be easily trapped into the local optimum is further solved. By the combination of the two intelligent optimization algorithms, the optimization capability is improved greatly; the tabu particle swarm algorithm based reactive power optimization method is much suitable for departments relevant to a power system and the like to implement reactive power optimization of the power distribution network.

The present invention relates to an image thermal apparatus including a flexible metallic sleeve, the inner peripheral surface of which contacts a heater. In order to provide increased durability for the sliding face of the heater, an imide resin that contains silicon nitride elementary particles is used to coat the sliding face of the heater.

A production for metal sulfide is carried by: 1) mixing elemental sulfur with metal or low metal sulfide in organic solvent and reacting at 100-500deg.C and 1-800Pa for 6-120 hrs. Its advantages include high safety, no pollution and low cost for catalyst and battery materials.

The present invention relates to an image thermal apparatus including a flexible metallic sleeve, the inner peripheral surface of which contacts a heater. In order to provide increased durability for the sliding face of the heater, an imide resin that contains silicon nitride elementary particles is used to coat the sliding face of the heater.

The invention discloses a particle swarm optimization method based on survival of the fittest and step-by-step selection. The method mainly comprises the steps that particles are divided to two sets in the operating process, the first set of particles are superior particles, and the second set of particles are inferior particles. A solution space is searched for in the global scope through a species, and the global searching ability is enhanced; after each time of evolution, m the best particles in the species are maintained, the position spaces of better particles of the m particles are selected as new solution spaces, new particles are selected to replace the position of poor particles in the species in the new solution spaces, in this way, the optimal particles can be approached step by step, and the optimal solution is found out. The searching ability of the particle swarm optimization method is enhanced, the defects that a fundamental particle swarm optimization algorithm easily falls into local extremum or premature convergence or stagnation are overcome, and the optical values of parameters to be optimized can be more accurately and quickly found out.

The invention discloses a power generation planning method for a power system with a pumped storage power station. The power generation planning method is characterized by comprising the following steps: firstly, making a repairing plan, and acquiring a load curve of the power system; secondly, under constraint conditions of load balance, set stressing and climbing limits, system spinning reserve and pumped storage power station capacity, establishing a model with the minimum sum of the power generating cost and the start-stop cost of all thermal power generating sets within a scheduling period as an objective; finally, solving according to a basic particle swarm algorithm under chaos control. By the power generation planning method, the problems that during calculation of a power generation planning model of the power system, convergence is poor and local optimum easily appears are effectively solved, so that a more reasonable power generation plan of the power system can be made.

The invention discloses an optimal configuration scheme of distributed power supply. According to the method, the benefits of power distribution operators are mainly considered from a planning perspective; the randomness of wind power generation is considered; a multi-target optimal configuration model, with the minimal active electrical energy loss, the minimal total voltage deviation and the minimal risk cost, of a power distribution network is built; multi-target normalization is realized by a fuzzy set theory; the problem that various sub-targets are different in dimension is not generated any more; the built optimal configuration model is determined by an adaptive mutation particle swarm optimization, so that a mutation operation is introduced; the condition that basic particle swarm optimization easily falls into local optimum is improved; finally, as an example, an IEEE 33 node power distribution system validates that the optimal configuration model of DG and selected adaptive particle swarm optimization (AMPSO) disclosed by the invention; and the obtained simulation result shows that the model and the adaptive particle swarm optimization adopted by the scheme are feasible and effective.

The invention discloses a power distribution network power supply power restoration method based on a photovoltaic power generation system, and the power distribution network power supply restoration method is characterized in that after a power grid is widely blacked out, and island division is conducted for a photovoltaic system, so that the non-fault blackout area is maximally powered on the premise of maintaining the power of important loads. The power distribution network power supply power restoration method comprises the steps of determining an after-failure photovoltaic power generation system island dividing scheme, and determining a segmental switch configuration position needing to be disconnected when the island dividing scheme is actuated; examining whether a failure branch downstream contains the photovoltaic power generation system or not after the failure happens, and switching the photovoltaic power generation system to be operated in an island form if the failure branch downstream contains the photovoltaic power generation system; finding a segmental position and a blackout area branch segmental switch position needing to be disconnected when the photovoltaic island is formed; adjusting the after-failure power distribution network structural information, searching a restorable route of a non-failure blackout area, determining the quantity of operable segmental switches and contact switches, and determining a basic particle vector; and solving a power distribution power restoration scheme of a non-failure blackout area outside the island according to a binary particle group optimization algorithm.

The present invention discloses a multi-metal multi-objective ore blending method based on an adaptive particle swarm algorithm. The method comprises: determining actual production requirements and indexes of ore blending of metal opencast mines; minimizing the transportation work and the grade deviation as the objective, and constructing a multi-metal multi-objective ore blending model; carryingout improvement on the basic particle swarm algorithm to obtain an adaptive multi-objective particle swarm algorithm; and using the adaptive multi-objective particle swarm algorithm to solve the multi-metal multi-objective ore blending model. The present invention provides an effective ore blending method for the production management of the multi-metal multi-objective ore blending, realizes complete description of the actual ore blending process of the multi-metal multi-objective opencast mines, and adopts an adaptive multi-objective particle swarm optimization algorithm to solve the problem,so that the solution of the multi-metal multi-objective model is more scientific, reasonable and practical; and the ore blending method can effectively achieve the equilibrium of the ore blending grade, reduce the transportation cost of the enterprise, and significantly improve the comprehensive utilization rate and economic benefit of the ore.

The present invention relates to a set of multi-doped cerium-activated scintillation materials of the solid solutions on the basis of the rare earth silicate, comprising lutetium and having compositions represented by the chemical formulas: (Lu2−w−x+2yAwCexSi1−y)1−zMexJjOq and (Lu2−w−x−2yAwCexSi1+y)1−zMezJjOq. The invention is useful for detection of elementary particles and nuclei in high-energy physics, nuclear industry; medicine, Positron Emission Tomography (TOF PET and DOI PET scanners) and Single Photon Emission Computed Tomography (SPECT), Positron Emission Tomography with Magnetic Resonance imaging (PET / MR); X-ray computer fluorography; non-destructive testing of solid state structure, including airport security systems, the Gamma-ray systems for the inspection of trucks and cargo containers.

The present invention concerns a catalyst comprising at least one crystalline material comprising silicon with a hierarchical and organized porosity and at least one hydrodehydrogenating element selected from the group formed by elements from group VIB and / or group VIII of the periodic table of the elements. Said crystalline material comprising silicon with a hierarchical and organized porosity is constituted by at least two spherical elementary particles, each of said particles comprising a matrix based on oxide of silicon, which is mesostructured, with a mesopore diameter in the range 1.5 to 30 nm and having microporous and crystalline walls with a thickness in the range 1.5 to 60 nm, said elementary spherical particles having a maximum diameter of 200 microns. The invention also concerns hydrocracking / hydroconversion and hydrotreatment processes employing said catalyst.

The present invention concerns a catalyst comprising at least one amorphous material comprising silicon with a hierarchical and organized porosity and at least one hydrodehydrogenating element selected from the group formed by elements from group VIB and / or group VIII of the periodic table of the elements. Said amorphous material comprising silicon with a hierarchical and organized porosity is constituted by at least two spherical elementary particles, each of said spherical particles comprising a matrix based on oxide of silicon, which is mesostructured, with a mesopore diameter in the range 1.5 to 30 nm and having amorphous and microporous walls with a thickness in the range 1.5 to 50 nm, said elementary spherical particles having a maximum diameter of 200 microns. The invention also concerns hydrocracking / hydroconversion and hydrotreatment processes employing said catalyst.

The invention provides an electric vehicle charging distribution method and apparatus. The method comprises the steps of establishing a charging uniform distribution target function by utilizing a charging station quantity, target charging power of the charging stations, an electric vehicle quantity, electric vehicle charging power, charging decision variables, charging journeys and charging time when a plurality of electric vehicles are distributed to a plurality of charging stations for charging; establishing constraint conditions of the charging decision variables and the charging journeys; under the constraint conditions, solving the charging uniform distribution target function by utilizing a basic particle swarm optimization algorithm to obtain charging decision results of the electric vehicles, wherein the charging decision results are used for distributing the electric vehicles to the charging stations for charging. According to the method and the apparatus, the demands of electric vehicle users and stable operation requirements of a power network can be met at the same time.

The invention relates to an efficient data compression technique, in particular to a vector code book quantizer which is used in speech coding and image compressing systems and is based on particle swarm. The technique of the invention is characterized in that the vector code book quantizer is designed according to the combined proposal of particle swarm optimization and simulated annealing; in the process of designing the vector code book quantizer, an empty cell processing proposal newly posted is adopted to solve the problem of empty cells. The vector code book quantizer based on the particle swarm of the invention can be realized by software simulation. According to the evaluation of unofficial hearing tests of speech which is obtained after the vector code book quantizer being coded and reconstructed through the adoption of speech data, the speech reconstructed by the newly posted method is better than the speech reconstructed based on the particle swarm optimization no matter in the aspect of clarity, naturalness or comprehensibility.

The invention discloses a machine learning recognition and process parameter optimization method for abrasive belt abrasion. The method comprises the following steps: S1, making a training set and a test set required by convolutional neural network training; S2, training a machine learning classification model based on a neural network; S3, an abrasive particle abrasion image on the surface of theabrasive belt is obtained; S4, identifying and distinguishing a wear region, an unworn region and a blocked region in the abrasive belt wear image through a machine learning classification model; S5,calculating the area and the area rate of each area; and S6, judging whether the process parameters are reasonable or not according to the area ratio of each part, and optimizing the existing parameters by adopting a basic particle swarm optimization algorithm. According to the method, the abrasion condition is identified through the model obtained through machine learning, and the process parameter optimization direction is predicted. The abrasive belt abrasion measuring and calculating process is simplified, intelligent image detection of the abrasive belt abrasion degree is achieved, the abrasive belt abrasion condition can be accurately, rapidly and conveniently measured, and good measuring precision is achieved.

A useable electromagnetic blue print of the structure of space is disclosed. The blue print comprises an irregular tetrahedral arrangement comprising of four isosceles triangular faces each having two angles of approximately 54.73561 degrees and one of approximately 70.5 degrees, the four triangles being arranged in two pairs, the paired triangles being connected along the longer edges of each of the triangles, the included angle between the two faces of the paired triangles being 90 degrees, the long edges of the two pairs of triangles being of the approximate ratio of 100:86.6 relative to the four shorter edges, and the long edges being located perpendicularly with respect to each other on opposite sides of the tetrahedral arrangement. The tetrahedral arrangement provides a modular component which is close-packable with three other similar adjoining modular irregular tetrahedral arrangements defining a specifically dimensioned octahedral arrangement. The outermost points of each tetrahedral and octahedral arrangement define nodal points such as the positions of four elementary particles wherein the magnetic and the electrical fields within certain materials and circuits can be constructively organised to perform a number of specific functions.

The present invention refers to a method for the precise measurement of dependency on amplitude and phase of a plurality of high frequency signals, preferably in the synchrotron accelerator of elementary particles. The essence of the solution according to the invention lies in that with a single measuring device and without any aliasing it is achieved a resolution of 0.2 micron and repeatability of measurements of 1 micron down to the lower frequency limit of a few MHz. A method according to the invention includes alternately directing, with a radio frequency (RF) switch, each analogue input signal to each of a plurality of RF processing units; amplifying each analogue input signal in each RF processing unit in order to adjust signals to the measuring range of a plurality of analog-digital (A / D) converters; directing each amplified analogue input signal to each of a plurality of A / D converters; converting the analogue signals to digital signals; directing the digital signals to a digital corrector; correcting the digital signals by means of correcting signals from the inverse models of evaluated systematic errors; collecting corrected digital signals in a digital switch and directing the ordered recombined number of digital signals to each of a plurality of digital receivers; and filtering the recombined number of digital signals in a plurality of low-pass filters.

A method and means to produce an antigravitational force for propulsion and / or levitation comprise a source of fundamental particles including electrons and a means to give the fundamental particles negative curvature; whereas, the gravitating body is comprised of matter of positive curvature where opposite curvatures provide a mutually repulsive antigravitational force. Electrons are given negative curvature by elastically scattering electrons of an electron beam from atoms such that negatively curved electrons (pseudoelectrons) emerge. The emerging beam of negatively curved electrons experience an antigravitational force, and (on the Earth) the beam moves upward (away from the Earth). To use this invention for propulsion or levitation, the antigravitational force of the electron beam is transferred to a negatively charged plate. The Coulombic repulsion between the beam of electrons and the negatively charged plate causes the plate (and anything connected to the plate) to lift. The craft is made to have angular momentum Which is tilted relative to the axis defined by the gravitational force such that acceleration tangential to the surface of a gravitating body is achieved via conservation of the angular momentum.

The invention relates to a thermal power generating unit system model parameter identification method. A self-adaptive thought, a Cauchy variation factor and a gradient guidance crossover theory are introduced to improve a basic particle swarm algorithm, parameters of an established model are identified, a difference value between actual operation data and model data is regarded as an algorithm fitness function value, model parameters are identified and optimized to obtain a model suitable for a system, a main throttle valve opening degree-power model, a combustion system and a load system, which are obtained through identification by adopting the improved self-adaptive Cauchy variation gradient guidance crossover particle swarm algorithm, have good effect of outputting fitting field actual data, a transfer function obtained through identification structurally conforms to theoretical analysis and conforms to actual operation conditions of the unit in the aspect of parameters, and the thermal power generating unit system model parameter identification method has good unit analysis and research value.

The invention discloses a distributed wind turbine generator system reactive power optimization strategy. The strategy includes original data inputting, simplex method initiation, load flow calculation, object function fitness value calculation, extreme updating, determining whether variation conditions have been met, variation operation, and determining whether the calculation has met terminating conditions. The method is based on particle swarm optimization algorithm, and proposes an improved particle swarm algorithm which changes the initiation method of particle swarm, introduces variation factors to iterative, and modifies the iterative formula and parameters of the fundamental particle swarm algorithm. According to the invention, the sum of transmission losses and average voltage irrelevance serves as a reactive optimization model of the object function, the reactive power limit of a double fed asynchronous wind power generator (DFIG) serves as constraining condition, and the improved particle swarm algorithm is utilized to resolve distributed wind farm reactive requirements and reactive distribution of each wind turbine generator system. Compared with convention control methods, the strategy is advantaged by cost and engineering practicality, and flexible and rapid control.

A method and device for measurement of dependency on amplitude and phase of a plurality of high frequency signals used primarily with a synchrotron accelerator of elementary particles, includes alternately directing, with a radio frequency (RF) switch, each analogue input signal to each of a plurality of RF processing units; amplifying each analogue input signal in each RF processing unit in order to adjust signals to the measuring range of a plurality of analogue digital converters; directing each amplified analogue input signal to each of a plurality of analogue digital converters; converting the analogue signals to digital signals; directing the digital signals to a plurality of amplification correctors; correcting the digital signals by means of correcting signals from an amplification equalizer; collecting corrected digital signals in a digital switch and directing the ordered recombined number of digital signals to each of a plurality of digital receivers; and filtering the recombined number of digital signals in a plurality of low-pass filters.

The invention discloses a vehicle state estimation method based on adaptive volume particle filter (ACPF), which comprises the following steps: firstly, constructing a high-dimensional nonlinear eight-degree-of-freedom vehicle dynamic model based on an unsteady state dynamic tire model; secondly, updating an importance density function of a basic particle filtering algorithm by utilizing an adaptive volume Kalman filtering algorithm so as to complete the design of the adaptive volume particle filtering algorithm; achieving high-precision online observation of key state variables such as roll angle and side slip angle of a vehicle by using vehicle-mounted sensor information and an ACPF algorithm; finally, building a Simulink-Carsim joint simulation platform for algorithm verification. The result shows that the algorithm state estimation precision is higher than that of a traditional unscented particle filter (UPF) algorithm, and the algorithm operation efficiency is higher than that ofthe UPF algorithm.

An artificial magnetic field and a natural gravitational field have cancellation or promotion interference effect at the quantity level with the same intensity according to a fundamental particle background procession magnetic field quantum gravity formula and a fundamental particle background procession magnetic field nature provided by a unified theory of ultimate segmentation, which is called the natural gravity field interference effect. A method for manufacturing and maintaining an artificial gravity field environment of weight loss or overweight, unilateral gravity occurrence, and the like by applying a coherent field interference mechanism and inherent technical parameters of the natural gravity field is called the interference method of the natural gravity field. The interference method of the natural gravity field can be realized into a natural gravity field interference device, which is short for a gravity machine according to the operation principle and the technical characteristic. Comparing the natural gravity field interference method with the other processes for manufacturing and maintaining weight loss or overweight and unilateral gravity occurrence, the invention has the technical characteristic of applying the coherent field interference mechanism and the inherent technical parameters of the natural gravity field. The so-called nature means natural essence and natural parameters.